Search Results (140)

This study examines the intersection of artificial intelligence-driven personal branding strategies and female entrepreneurship within Indonesia’s unique hijabi startup ecosystem. Through a mixed-methods approach combining sentiment analysis of 2847 social media posts, in-depth interviews with 35 hijabi entrepreneurs, and machine learning analysis of branding patterns, this research reveals how AI technologies can be leveraged to create culturally sensitive personal branding frameworks for Muslim female entrepreneurs. The findings demonstrate that successful hijabi entrepreneurs employ distinct AI-enhanced communication strategies that balance religious identity, professional credibility, and market positioning. The study introduces the “Halal Personal Branding Framework,” a novel theoretical model that integrates Islamic values with contemporary digital marketing practices. Results indicate that AI-driven personal branding increases startup funding success rates by 34% and market reach by 58% among hijabi entrepreneurs when culturally appropriate algorithms are employed. This research contributes to entrepreneurship communication theory while providing practical guidelines for developing inclusive AI systems that respect religious and cultural diversity in the digital economy. Full article

In October 2024, a DANA (Isolated Depression at High Levels) triggered torrential rains across the Valencian Community, causing 227 deaths, severe infrastructure damage, and economic losses estimated at €17.8 billion. In this context of crisis, startups, despite having fewer resources and less experience than large corporations, played a significant role in crisis communication, shaping public perception and operational continuity. This study explores the communication strategies adopted by startups during and after the disaster, focusing on their activity on Instagram, TikTok, and Facebook between October 2024 and January 2025. Using a mixed-methods approach, we conducted a quantitative analysis of digital discourse through the Fanpage Karma tool, assessing metrics such as engagement, reach, and posting frequency. Sentiment analysis was performed using GPT-4, an advanced natural language processing model, and in-depth interviews with startup representatives provided qualitative insights into reputational impacts. The findings reveal that startups which aligned their discourse with the social context, prioritizing transparency and emotional proximity, enhanced their visibility and credibility. These results underscore how effective crisis communication not only mitigates reputational risk but also strengthens the local entrepreneurial ecosystem through trust-building and social responsibility. Full article

Dietary choices and patterns have enormous consequences along the lines of individual, community, and planetary health. Excess meat consumption has been linked to chronic disease risk, and at large scales, the underlying industries maintain a massive environmental footprint. For these reasons, public and planetary health experts are unified in emphasizing a whole or minimally processed plant-based diet. In response, the purveyors of ultra-processed foods have added “meat alternatives” to their ultra-processed commercial portfolios; multinational corporations have been joined by “start-ups” with new ultra-processed meat analogues. Here, in our Viewpoint, we revisit the 1990s food industry rhetoric and product innovation, a time in which multinational corporations pushed a great “low-fat transition.” We focus on the McLean Deluxe burger, a carrageenan-rich product introduced by the McDonald’s Corporation in 1991. Propelled by a marketing and media-driven fear of dietary fats, the lower-fat burger was presented with great fanfare. We reflect this history off the current “great protein transition,” a period once again rich in rhetoric, with similar displays of industry detachment from concerns about the health consequences of innovation. We scrutinize the safety of carrageenan and argue that the McLean burger should serve as a cautionary tale for planetary health and 21st century food innovation. Full article

We explored the use of artificial intelligence (AI) in enhancing the English proficiency of students in the English as a Foreign Language (EFL) course through a startup product development curriculum. In the course, real-world business scenarios of startup companies were offered for students to analyze English communication skills on crowdfunding platforms and in product promotional videos. The EFL students used entrepreneurial skills to create and present their product videos in a team to the class who acted as potential investors. Pre- and post-test analyses were conducted to assess the impact of AI-assisted learning on enhancing English listening and reading ability. Significant improvements were observed, suggesting AI-enhanced entrepreneurial experiences and the listening and reading ability of the EFL students. Full article

The recirculating aquaculture system (RAS) has been rapidly adopted worldwide in recent years due to its high productivity, good stability, and good environmental controllability (and therefore friendliness to environment and ecology). Nevertheless, the effluent from seawater RAS contains a high level of ammonia nitrogen which is toxic to fish, so it is necessary to overcome the salinity conditions to achieve rapid and efficient nitrification for recycling. The moving bed biofilm reactor (MBBR) has been widely applied often by using PE fillers for efficient wastewater treatment. However, the start-up of MBBR in seawater environments has remained a challenge due to salinity stress and harsh inoculation conditions. This study investigated a new PE-filler surface modification method towards the enhanced start-up of mariculture MBBR by combining liquid-phase oxidation and maifanstone powder. The aim was to obtain a higher porous surface and roughness and a strong adsorption and alkalinity adjustment for the MBBR PE filler. The hydrophilic properties, surface morphology, and chemical structure of a raw polyethylene filler (an unmodified PE filler), liquid-phase oxidation modified filler (LO-PE), and liquid-phase oxidation combined with a coating of a maifanstone-powder-surface-modified filler (LO-SCPE) were first investigated and compared. The results showed that the contact angle was reduced to 45.5° after the optimal liquid-phase oxidation modification for LO-PE, 49.8% lower than that before modification, while SEM showed increased roughness and surface area by modification. Moreover, EDS presented the relative content of carbon (22.75%) and oxygen (42.36%) on the LO-SCPE surface with an O/C ratio of 186.10%, which is 177.7% higher than that of the unmodified filler. The start-up experiment on MBBRs treating simulated marine RAS wastewater (HRT = 24 h) showed that the start-up period was shortened by 10 days for LO-SCPE compared to the PE reactor, with better ammonia nitrogen removal observed for LO-SCPE (95.8%) than the PE reactor (91.7%). Meanwhile, the bacterial community composition showed that the LO-SCPE reactor had a more diverse and abundant AOB and NOB. The Nitrospira has a more significant impact on nitrification because it would directly oxidize NH₄⁺-N to NO₃⁻-N (comammox pathway) as mediated by AOB and NOB. Further, the LO-SCPE reactor showed a higher NH₄⁺-N removal rate (>99%), less NO₂⁻-N accumulation, and a shorter adaption period than the PE reactor. Eventually, the NH₄⁺-N concentrations of the three reactors (R1, R2, and R3) reached <0.1 mg/L within 3 days, and their NH₄⁺-N removal efficiencies achieved 99.53%, 99.61%, and 99.69%, respectively, under ammonia shock load. Hence, the LO-SCPE media have a higher marine wastewater treatment efficiency. Full article

Embedded system networks are widely deployed across various domains and often perform mission-critical tasks, making it essential for all nodes within the system to be trustworthy. Traditionally, each node is equipped with a discrete Trusted Platform Module (dTPM) to ensure network-wide trustworthiness. However, this study proposes a cost-effective system architecture that deploys software-based TPMs (SWTPMs) on the majority of nodes, while reserving dTPMs for a few central nodes to maintain overall system integrity. The proposed architecture employs IBMACS for system integrity reporting. In addition, a database-based anomaly detection (AD) agent is developed to identify and isolate untrusted nodes. A traffic anomaly detection agent is also introduced to monitor communication between servers and clients, ensuring that traffic patterns remain normal. Finally, a custom measurement kernel is implemented, along with an activation agent, to enforce a measured boot process for custom applications during startup. This architecture is designed to safeguard mission-critical embedded systems from malicious threats while reducing deployment costs. Full article

Startups in the clean energy and environmental technology (CEET) sector can develop sustainable innovations, but mobilizing private finance has been difficult. As the venture capital (VC) investment model was found to be not well-suited for the CEET startups, diverse types of investors have received more attention. However, since previous studies have been dominated by a VC-centric perspective in the US and have overlooked collaborative relationships, the roles of various CEET investors have not been systematically analyzed. This study aims to analyze the diverse investors in the CEET investor network formed through co-investment syndication, using Japan as an underexplored regional context. Based on Japan’s comprehensive data from 2008 to 2022, this study examines the evolution, structure, and communities of the network. The analysis identified the development stages of the investor network: the formation stage (2008–2012), the expansion and diversification stage (2013–2017), and the stable growth stage (2018–2022). The results confirmed the strong influence of VCs, while a community analysis suggested the bridging role of governmental venture capital. The findings based on the CEET investor network contribute to expanding both the theoretical understanding and practical implications for overcoming the financing difficulties of CEET startups to address the climate change crisis. Full article

The evolution of aircraft power systems has been driven by increasing electrical demands and advancements in aviation technology. Background: This study provides a comprehensive review and experimental validation of on-board electrical network development, analyzing power management strategies in both conventional and modern aircraft, including the Mi-24 helicopter, F-22 multirole aircraft, and Boeing 787 passenger airplane. Methods: The research categorizes aircraft electrical systems into three historical phases: pre-1960s with 28.5 V DC networks, up to 2000 with three-phase AC networks (3 × 115 V/200 V, 400 Hz), and post-2000 with 270 V DC networks derived from AC generators via transformer–rectifier units. Beyond theoretical analysis, this work introduces experimental findings on hybrid-electric aircraft power solutions, particularly evaluating the performance of the Modular Power System for Aircraft (MPSZE). The More Electric Aircraft (MEA) concept is analyzed as a key innovation, with a focus on energy efficiency, frequency stability, and ground power applications. The study investigates the integration of alternative energy sources, including photovoltaic-assisted power supplies and fuel-cell-based auxiliary systems, assessing their feasibility for aircraft system checks, engine startups, field navigation, communications, and radar operations. Results: Experimental results demonstrate that hybrid energy storage systems, incorporating lithium-ion batteries, fuel cells, and photovoltaic modules, can enhance MEA efficiency and operational resilience under real-world conditions. Conclusions: The findings underscore the importance of MEA technology in the future of sustainable aviation power solutions, highlighting both global and Polish research contributions, particularly from the Air Force Institute of Technology (ITWL). Full article

The transformation of energy markets is at a crossroads in the search for how they must evolve to become ecologically friendly systems and meet the growing energy demand. Currently, methodologies based on bibliographic data analysis are supported by information and communication technologies and have become necessary. More sophisticated processes are being used in energy systems, including new digitalization models, particularly driven by artificial intelligence (AI) technology. In the present bibliographic review, 342 documents indexed in Scopus have been identified that promote synergies between AI and the energy transition (ET), considering a time range from 1990 to 2024. The analysis methodology includes an evaluation of keywords related to the areas of AI and ET. The analyses extend to a review by authorship, co-authorship, and areas of AI’s influence in energy system subareas. The integration of energy resources, including supply and demand, in which renewable energy sources play a leading role at the end-customer level, now conceived as both producer and consumer, is intensively studied. The results identified that AI has experienced notable growth in the last five years and will undoubtedly play a leading role in the future in achieving decarbonization goals. Among the applications that it will enable will be the design of new energy markets up to the execution and start-up of new power plants with energy control and optimization. This study aims to present a baseline that allows researchers, legislators, and government decision-makers to compare their benefits, ambitions, strategies, and novel applications for formulating AI policies in the energy field. The developments and scope of AI in the energy sector were explored in relation to the AI domain in parts of the energy supply chain. While these processes involve complex data analysis, AI techniques provide powerful solutions for designing and managing energy markets with high renewable energy penetration. This integration of AI with energy systems represents a fundamental shift in market design, enabling more efficient and sustainable energy transitions. Future lines of research could focus on energy demand forecasting, dynamic adjustments in energy distribution between different generation sources, energy storage, and usage optimization. Full article

This paper investigates points of vulnerability in the decisions made by backers and campaigners in crowdfund pledges in an attempt to facilitate a sustainable entrepreneurial ecosystem by increasing the rate of good projects being funded. In doing so, this research examines factors that contribute to the success or failure of crowdfunding campaign pledges using eXplainable AI methods (SHapley Additive exPlanations and Counterfactual Explanations). A dataset of completed Kickstarter campaigns was used to train two binary classifiers. The first model used textual features from the campaigns’ descriptions, and the second used categorical, numerical, and textual features. Findings identify textual terms, such as “stretch goals”, that convey both elements of risk and ambitiousness to be strongly correlated with success, contrary to transparent communications of risks that bring forward worries that would have otherwise remained dormant for backers. Short sentence length, in conjunction with high term complexity, is also associated with campaign success. We link the latter to signaling theory and the campaigners’ projection of knowledgeability of the domain. Certain numerical data, such as the project’s duration, frequency of post updates, and use of images, confirm previous links to campaign success. We enhance implications through the use of Counterfactual Explanations and generate actionable recommendations on how failed projects could become successful while proposing new policies, in the form of nudges, that shield backers from points of vulnerability. Full article

This paper presents the design and the performance of a wide tuning-range millimeter-wave (mm-wave) two-core class-C 60 GHz VCO in 40 nm CMOS process, which can be integrated into wireless communication transceivers and radar sensors. The proposed architecture consists of a two-core 30 GHz fundamental VCO, a gain-boosted frequency doubler and an adaptive bias configuration. The two-core fundamental VCO structure achieves frequency generation in the vicinity of 30 GHz, where each VCO core targets a different frequency band. The two bands have sufficient overlap to accommodate for corner variations providing a large continuous tuning range. The desired frequency band is selected by activating or deactivating the appropriate VCO core, resulting in a robust switchless structure. This approach enables a considerably broad tuning range without compromising phase noise performance. Furthermore, the proposed topology utilizes an adaptive bias mechanism for robust start-up. Initially, the selected VCO core begins oscillating in class-B mode, and subsequently it transitions into class-C operation to offer improved performance. From post-layout simulations, after frequency doubling, the low-band VCO covers frequencies from 50.25 to 60.40 GHz, while the high-band VCO core spans frequencies from 58.8 to 73 GHz, yielding an overall tuning range of 36.92%. Owing to the gain-boosting topology, output power exceeds −14.2 dBm across the whole bandwidth. Simulated phase noise remains better than −92.1 dBc/Hz at a 1 MHz offset for all bands. Additionally, the two VCO cores never operate simultaneously, aiding in power efficiency. Full article

Circular Economy (CE) models have gained attention in the academic community for their ability to promote sustainability and efficiency in resource use. It promotes advances in the traditional linear economy and offers innovative solutions to environmental issues. In this context, start-ups play a key role in implementing Circular Business Models (CBMs), leading the transition to more sustainable practices and positively impacts on the market and the environment. In the current academic literature, there are relevant studies on the implementation of the CE in traditional companies. Still, discussions on how start-ups transition from linear economy to circular business models remain limited. To address this gap, we conducted a systematic literature review on how start-ups design and adapt the linear economy to their circular business models. Our methodology followed the PRISMA 2020 protocol, thoroughly searching the Scopus, Science Direct, and Web of Science databases, resulting in 42 articles. The findings highlight the crucial role of Circular Start-Ups (CSUs) in the transition to a Circular Economy, identifying the challenges and opportunities they face and the internal and external barriers they need to overcome to ensure long-term sustainability. Furthermore, this study highlights the existing gaps in the literature and suggests key areas for future research. Full article

This study explores AnMBR technology as a promising method for treating wastewater from the meat-processing industry by analysing its characteristics and impact under continuous feeding. The solids were retained, utilising an ultrafiltration membrane with a pore size of 0.2 µm, and the efficacy of reducing the organic load was evaluated. Although the COD removal rate decreased from 100% at an OLR of 0.71 g/(L*d) to 73% at an OLR of 2.2 g/(L*d), maximum methane yields were achieved at the highest OLR, 292.9 Nm³/t (COD) and 397.8 Nm³/t (VS) per loaded organics and 353.1 Nm³/t (COD) and 518.7 Nm³/t (VS) per removed organics. An analysis of the microbial community was performed at the end of the experiment to assess the effects of the process and the substrate on its composition. The AnMBR system effectively converts meat-processing wastewater into biogas, maintaining high yields and reducing the loss of dissolved methane in the permeate, thanks to a temperature of 37 °C and high salt levels. AnMBR enables rapid start-up, efficient COD removal, and high biogas yields, making it suitable for treating industrial wastewater with high organic loads, enhancing biogas production, and reducing methane loss. Challenges such as high salt and phosphate levels present opportunities for a wider use in nutrient recovery and water reclamation. Full article

This study explores the impact of incorporating conductive materials and bioelectrochemical systems (BES) on the efficiency of anaerobic digestion (AD) of sewage sludge. The research consists of two phases: biodegradability tests using 3D-printed polylactic acid-based conductive fillers (PLA/Carbon Black and PLA/Graphene) and semi-continuous assays integrating an external BES into the AD process. Results from biodegradability tests indicate that conductive fillers enhance around 50% methane production during the start-up phase, with microbial communities adapting over time to reduce variability in methane yields. Moreover, as the experiment progressed, the methane yields of the digesters with and without fillers became equal. Semi-continuous experiments demonstrate that BES integration improves process stability and methane production by achieving a 5–10% improvement in the amount of methane in the biogas throughout the entire operation, even under high organic loads, by facilitating diverse electron transfer pathways. The challenges of BES operation highlight the need for optimized designs to ensure scalability. Microbial analyses reveal that BES application shifts methanogenic pathways, favouring acetoclastic methanogenesis. Overall, the findings underscore the potential of conductive materials and BES to improve biogas quality and production, contributing to sustainable wastewater management and renewable energy generation. Full article

Anaerobic digestion (AD) is a well-established technology for the sustainable conversion of agricultural organic by-products and waste into bioenergy. Temperature is crucial for optimizing methane production through inocula preservation and reactor start-up in AD. The preservation of inocula induced by temperature has rarely been assessed from an engineering perspective. There has also been limited exploration of the influence of high-to-moderate temperature transition on the initiation of AD. This study employed continuous mesophilic AD reactors with potential engineering applications to conduct revival tests. These tests evaluated the methane production activity of sludge stored at different temperatures and investigated the impact of high-temperature initiation on mesophilic AD. Additionally, we elucidated the correlation between these assessments and microbial diversity as well as composition. The results indicated that bacterial diversity was higher in the inoculum stored at 35 °C compared to 15 °C, ensuring a stable start-up operation of the mesophilic AD. The richness of the bacteria and diversity of the archaea remained stable during the transition from high to mesophilic temperatures. This was conducive to enhancing methanogenic activity of mesophilic AD initiated at 55 °C. The continuously operated AD system showed significant differences in microbial composition compared to its inoculum. Increased abundance of Coriobacteriaceae and Prevotellaceae led to propionate and butyrate accumulation, respectively, reducing AD operational capacity. Methanogenic archaea were less diverse in AD initiated with low-temperature preserved inoculum compared to that with a medium temperature. Streptococcaceae induced by high temperarure could promote AD stability. Hydrogenotrophic methanogens had a competitive advantage in mesophilic AD due to their prior exposure to high-temperature initiation, possibly influenced by Thermotogaceae. Full article